Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT

model updating [60, 55, 12] and is addressed in a future section.
Hardware Tuning
The hardware simulation is tuned in real time with the barrier steepest descent al-
gorithm (BSD) and simulated annealing (SA). The tuning configuration from the
model-only method that resulted in the best performance (in this case, nominal model
tuning) is used as the starting point. The resulting tuning parameters, tuned perfor-
mance and required number of hardware tests are listed in the table in Figure 4-10.
Although each method resulted in a different tuning mass configuration, both suc-
ceeded in bringing performance below the requirement. However, in order to achieve
this goal a large number of tests, more than 2000 in the case of SA, are required.
The results are shown graphically in the lower figure, Figure 4-10(b). The bar
chart shows the number of function evaluations required for each method. In this
example, the barrier method found a working configuration much more quickly than
simulated annealing. Simulated annealing takes a long time since it is a random
search and is not directed by gradient information. The lower subplot shows the
performance results obtained by each algorithm. The solid line is the requirement,
and the dotted lines indicates the nominal hardware performances. It is clear that
both algorithms succeed in meeting the requirement.
4.3 Isoperformance Updating for Tuning
In the previous section tuning methods ranging from those that use only the model to
others that reject the model and tune directly on hardware are explored. It is shown
that a trade exists between cost and reliability. The model-only methods are low-
cost since only one hardware test is necessary. The tuning optimization is done using
only the model and the resulting tuning parameters are then applied to the hardware.
However, since these methods rely only on a model that is uncertain and consequently
not exact they do not always succeed in tuning the hardware within performance. In
fact, for the hardware simulation considered, the tuned hardware performance is
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